The rapid development of information technology brings in “Big Data” era, which has altered urban spatial organization and innovated the research method for urban spatial structure. Conventional analysis for urban spatial structure originates from the material space and falls on the material space simultaneously. Since mobile phone signal big data under the information era can not only reflect the morphological situation of urban space directly and genuinely but also allow the research to originate from human and fall on space, so the research for urban space is not only limited to material space. Thus, in this Big Data era, research on urban spatial structure by using information data provides a new research direction and idea for existing researches on urban space, and poses a significant meaning on reconstructing and enriching the urban planning discipline theory, on directing urban planning and construction.
Until now, there are a lot of definitions for urban spatial structure circle in urban planning field, which is an important constituent part of planning practice for empirical analysis of each city. However, current definition method being mainly based on urban static spatial structure and being conducted mainly from static material space has a single applicable range and is difficult to track the dynamic urban structure. In summary, current definition for urban spatial structure circle is not suited for continuity analysis on dynamic spatial structure, and it has many drawbacks primarily comprising:    (1) preliminary survey costs a lot of manpower, material and financial resources, and conducts for a relatively long time period;    (2) since it costs too much and has a large time interval of survey, the data update may not reflect the actual situation of a city in time;    (3) inputting results from survey needs a heavy workload, at the same time, the accuracy and standardization may not remain uniform with a possibility of man-made error, so it can't support an optimized strategy of urban planning.
This method is commonly suited for circle analysis of urban static spatial structure, but hard to be continuous in the time dimension.